SA Schools data exploration

Overview

Data exploration using the data prepared by combining the “schools master lists” from the Department of Basic Education website for schools in South Africa.

# LIBRARIES ----------------------------------------------------------------------------------------
library(dplyr)
library(here)
library(ggplot2)
library(plotly)
# READ DATA ----------------------------------------------------------------------------------------
sa_schools <- readRDS(here::here("data/03_sa_schools.RDS"))

# VISUALISE ----------------------------------------------------------------------------------------
p <- ggplot(sa_schools, aes(x = Learners)) +
  geom_histogram() +
  labs(title='Histogram of no. of learners',
       x= 'No. of learners', y = 'School count')
ggplotly(p)

`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Removed 309 rows containing non-finite values (stat_bin).

p <- ggplot(sa_schools, aes(x = Educators)) +
  geom_histogram() +
  labs(title='Histogram of no. of educators',
       x= 'No. of educators', y = 'School count')
ggplotly(p)

`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Removed 683 rows containing non-finite values (stat_bin).

ggplotly(p)

Removed 1326 rows containing non-finite values (stat_count).